An economic study of controlled release urea and split applications of nitrogen as compared with non-coated urea under conventional and reduced tillage management
Bibliographic record
Abstract
Khakbazan, M., Grant, C. A., Finlay, G., Wu, R., Malhi, S. S., Selles, F., Clayton, G. W., Lupwayi, N. Z., Soon, Y. K. and Harker, K. N. 2013. An economic study of controlled release urea and split applications of nitrogen as compared with non-coated urea under conventional and reduced tillage management. Can. J. Plant Sci. 93: 523-534. To evaluate the use of controlled-release urea (CRU) as a beneficial management practice for nitrogen management of wheat, barley, and canola, a multi-location study was conducted from 2004 to 2006 in a range of agro-environments across western Canada. The objective was to evaluate the relative economic performance of CRU and non-coated urea (NCU) for their effects on seed yield and quality, costs and net revenue (NR) using conventional tillage (CT) and reduced tillage (RT) management under varying environmental conditions. The NR was estimated as the income remaining after paying for all cash costs, ownership costs on machinery and buildings, and labour. The main factor affecting crop yield and NR was N application rate. In general, application of NCU produced similar or higher net revenues than that of CRU, split fertilizer applications or a blend of NCU and CRU. There were some limited situations where the use of split applications, CRU or CRU in a blend with the NCU increased crop yield as compared with NCU; however, the increased yield was not sufficient to cover the extra costs of CRU or the split application. The impact of tillage system on crop yield and NR was not consistent. Net revenue was higher under CT than RT for certain crops in some regions, but not in all regions or for all crops. Overall, NR analysis indicated that use of CRU did not provide an economic benefit over the use of NCU.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".